Are you ready for the AI-powered future?
The AI & Algorithm Auditor Certification Program, developed by BABL AI, equips professionals with the skills to evaluate and ensure the responsible development and deployment of AI systems. This certification is globally recognized for its rigor and emphasis on the ethical, technical, and governance challenges of algorithmic systems.
🌟 Comprehensive Training
Participants engage with five core courses that cover:
- Algorithms, AI, & Machine Learning: Learn foundational AI concepts and techniques to perform risk analysis and governance.
- Algorithmic Risk & Impact Assessments: Master the art of identifying risks and creating transparent narratives for AI systems.
- AI Governance & Risk Management: Explore regulatory frameworks, governance principles, and emerging AI laws.
- Bias, Accuracy & the Statistics of AI Testing: Dive into technical evaluation methods, from bias detection to performance metrics.
- Algorithm Audit & Assurance: Develop expertise in audit methodologies, assurance engagements, and compliance standards like ISAE 3000.
📈 Professional Certification
Completion of the program demonstrates competency in conducting algorithm audits, performing risk assessments, and evaluating AI systems for compliance with global regulations like the EU AI Act and NYC Local Law 144. Certified professionals adhere to BABL AI's commitment to transparency, ethical AI use, and human flourishing.
🛠️ Real-World Applications
Graduates are prepared to audit high-risk AI systems, design risk management frameworks, and contribute to the ethical oversight of AI technologies. The program includes a capstone project, challenging participants to apply their knowledge to complex, real-world scenarios.
🌍 Global Relevance
BABL AI’s certification is trusted by "Big Four" firms, government agencies, and certification bodies. It aligns with emerging standards like NIST’s AI Risk Management Framework and ISO 42001, positioning professionals to navigate the evolving landscape of AI assurance.
This certification is ideal for auditors, AI governance specialists, and risk management professionals seeking to lead in the field of Responsible AI. Earning this credential signals your expertise in safeguarding the integrity and accountability of algorithmic systems.
Context
Algorithm auditing is a critical component of ensuring the safe and ethical development and deployment of artificial intelligence (AI) systems. As AI becomes more prevalent and integrated into various aspects of our lives, like in the rapid adoption of generative AI and large language models like ChatGPT, it is important to ensure that these systems are transparent, fair, and accountable.
Algorithm auditing involves examining algorithmic systems and their governance to ensure that ethical, safety, and compliance risks are sufficiently managed. By conducting independent audits, algorithm auditors can provide assurance to stakeholders that these systems are operating as intended, promote transparency and accountability, and further BABL’s mission of promoting human flourishing in the age of AI.
In order to fulfill this mission, algorithm auditors need a number of skills and capabilities, many of which fall outside the standard audit/assurance skillset. Current financial audit and assurance standards are critically important for maintaining independence and professional conduct, however, further capabilities are needed to deal with the complex sociotechnical systems in which modern AI and machine learning algorithms are embedded This is due to a) the rapid advance of the underlying technology, b) our rapidly evolving understanding of the ways these systems can affect society (both negatively and positively), and c) the fact that sufficient knowledge of (a) and (b) is needed to mitigate risk when evaluating algorithmic systems.
What this training is:
The objective of this training is to equip auditors with sufficient knowledge to identify relevant risks of using algorithmic systems, best practices for the governance of such systems, and the common techniques and workflows that are involved in modern AI/ML development. This knowledge will be used to assess the risk of material misstatement while evaluating audit documentation, under the supervision of a more experienced auditor, and is meant to lay the foundation for further on-the-job learning opportunities (either at BABL AI or other algorithm auditing firms).
What this training is not:
This training is not meant to encompass all knowledge and competencies needed to perform algorithm auditing in the absence of supervision or oversight from a more experienced auditor.
Who this training if for:
This program is developed for AI governance, risk, and compliance professionals needing to perform, e.g., AI risk or impact assessments within companies using or developing high-risk AI systems. This kind of training is important for companies trying to conform with:
- The EU AI Act
- Digital Services Act
- ISO 42001
- Auditors for ISO 42001 (see ISO 42006)
- NIST AI RMF
Other groups that would find this certification useful:
- Consultants in AI Ethics and Governance
- Procurement specialists who are concerned about risks due to AI vendors
- Employees at VC firms that want to incorporate AI risks into their due diligence process
Program Courses:
- Algorithms, AI, & Machine Learning
- Algorithmic Risk & Impact Assessments
- AI Governance & Risk Management
- Bias, Accuracy, & the Statistics of AI Testing
- Algorithm Auditing & Assurance
- AI & Algorithm Auditor Capstone Project and Exit Exam
About the Instructor
Dr. Shea Brown, CEO and Founder of BABL AI: Shea is an internationally recognized leader in AI and algorithm auditing, bias in machine learning, and AI governance. He has testified and advised on numerous AI regulations in the US and EU. He is a Fellow at ForHumanity, a non-profit working to set standards for algorithm auditing and organizational governance of artificial intelligence. He is also a founding member of the International Association of Algorithmic Auditors, a community of practice that aims to advance and organize the algorithmic auditing profession, promote AI auditing standards, certify best practices and contribute to the emergence of Responsible AI. He has a PhD in Astrophysics from the University of Minnesota and is currently a faculty member in the Department of Physics & Astronomy at the University of Iowa, where he has been recognized for his teaching excellence from the College of Liberal Arts & Sciences.
Tony - Model risk, Global Bank
"What I particularly appreciated about this program was its ability to strengthen my understanding in areas where my knowledge was previously relatively limited. The content was not only thoroughly well-balanced, covering both foundational and advanced topics, but also very engaging and interesting. The unique nature of the program really stood out; despite my extensive search for similar courses, none matched the depth and relevance in risk management offered here."
Luna - AI Product Manager
"Throughout the course, I gleaned a framework for the science, laws and critical thinking behind AI auditing. Dr. Shea Brown and his team provided an excellent balance of theoretical knowledge and practical applications so that I could feel confident in working with a team to identify, analyze and test risks of the systems all around us… BABL AI created a welcoming environment for people regardless of professional background. I felt confident in scaling my knowledge and skills without a science background and also in my lived experience being respected as part of the auditing process."
Mert - Auditor & Educator
"I have done many training programs in the field of AI Ethics and AI Assessments and/or Audits and I can say that the AI and Algorithm Auditor Certificate Program from BABL AI is definitely one of the best on the market. Prof. Shea Brown does an excellent job both as Instructor and Mentor. Shea and the BABL AI team were always kind and helpful. We did a cohort based training as the first movers, I must admit that the cohort was amazing and made the training a great journey but it is also suitable for individuals who can do it on their own, adjusting their pace with their other responsibilities."
Frequently Asked Questions
How many courses are in this program?
There are 5 courses in the certificate program (listed below), plus a capstone project and certification exam.
What if I just want to take one or two courses?
Each course can be purchased separately by clicking on the course link below.
How long will it take me to complete this program?
Each course is approximately 2 weeks long and will take about 30 hours of total effort per course. The length of time to complete the entire program depends on whether you are taking it synchronously or asynchronously.
Can I get a refund if I'm unhappy with my purchase?
As stated in Teachable's Terms of Use, there is a 14-day student refund policy.
Will I get a certificate for these courses?
Yes. For each course that is completed with over 70% of the total points, you will get a certificate of completion. If you complete all 5 core courses in the program, you will receive an AI and Algorithm Auditing Certificate.
Will I get a Certification for this course?
Yes, you can obtain a Certification after an exam and exit interview.
What are the prerequisites for this program?
None for the certificate. Anyone may take the courses and receive a certificate of completion with a score of 70% or above. For those seeking certification, however, the prerequisites are:
- Have completed an undergraduate degree or equivalent coursework (contact [email protected] if seeking a waver)
- Basic competency in mathematics including algebra, basic calculus, and introductory statistics
Will my employer pay for this program?
Many employers will pay for you to get professional development, especially if the learning objectives will expand your ability to perform at work. See here for advice on how to ask your employer to pay for an online course.
Will this program be useful for auditing clients in the EU?
Our intention with the AI Auditor Certificate Program is to make it as applicable as possible to both US and EU organizations. BABL AI is actively tracking and participating in a number of efforts related to both the EU Digital Services Act and the EU AI Act. Our auditing methodology is aligned with international assurance standards used by the "Big Four" auditing firms, and they're likely the ones that will be adopted for the DSA/AIA (see our recommendations to the European Commission).
Is this program useful if I don't want to be an AI Auditor?
The courses in this program are meant to provide general and transferable skills in areas of AI governance, risk assessment, and technical testing of AI systems which are applicable in corporate, government, or civil society settings.
The only audit-specific course is "Algorithm Auditing & Assurance".
Bundle Contents
Showcase courses, digital downloads and coaching in your Bundle.
